• Duration

    40 Minutes

  • Level

    Beginner

  • Course Type

    Short Course

What you'll Learn

  • Understanding the core concepts behind RAG and agentic systems for scalable LLM applications.

  • Techniques for integrating LLMs into industry-grade production environments.

  • Practical deployment strategies with UI integrations using tools like Streamlit or other frontend frameworks.

  • How to evaluate the performance of LLMs in real-world applications and ensure reliability at scale.

Who Should Enroll?

  • Individuals: AI/ML engineers, developers, and data scientists will master scalable LLM integration. Product managers, leaders, and entrepreneurs can leverage RAG and agentic systems for AI deployment and optimization.

  • Aspiring Students: AI/ML, Data Science, and NLP students will gain hands-on LLM deployment experience. Research scholars and aspiring AI developers can explore RAG, agentic systems, and LLM evaluation for industry readiness.

About the Instructor

Anuj Saini, AI Research Scholar - Université de Montréal

Anuj Saini is a Subject Matter Expert with over 15 years of industry experience in Natural Language Processing, Search Technologies, Statistics, Analytics, Modelling, Data Science, Data Mining, and Machine Learning. He has a proven track record in developing systems based on NLP, Machine Learning, and Cloud Technologies. You can reach him on LinkedIn.
About the Instructor

FAQ's

  • What is RAG?

    Retrieval-Augmented Generation (RAG) enhances LLM responses by retrieving relevant external data before generating text. This improves accuracy, reduces hallucinations, and enables real-time knowledge updates.

  • What is an Agentic System?

    An agentic system enables AI agents to autonomously perform tasks, make decisions, and interact with users or systems using reasoning, planning, and adaptive learning.

  • Will I receive a certificate upon completing the course?

    Yes, the course provides a certification upon completion.

  • Will this course include hands-on exercises?

    Yes, the course covers practical deployment strategies, including UI integrations using Streamlit or other frontend frameworks, ensuring you gain applied experience.